This paper suggests a plausible microstructural connection between rational speculative activity and exchange rate volatility. When Friedman (1953) claimed that rational speculators must smooth exchange rates, he excluded interest rate differentials from his interpretation of speculator behavior. Informed, rational speculators who consider interest differentials will magnify the exchange rate effects of interest shocks and could increase overall exchange rate volatility. This connection between speculators and volatility, which does not rely on asymmetric information, is structural because speculators affect the exchange rate’s generating process. Rational speculation is stabilizing at low levels of speculative activity and destabilizing at high levels. (J.E.L. codes F31, G12.

DRAFT It is generally recognized that volatility in the prices of securities is due, in part, to traders continuously revising their preference sets in response to the arrival of unanticipated information. In particular, traders may update beliefs about the value of an asset in response to information on both market microstructure and the macro-economy. We argue that the microstructure characteristics of the Trinidad and Tobago Stock Exchange (TTSE) are consistent with serial correlation, volatility clustering, and nonlinearity in stock returns. The underlying behavioural patterns arise because informed traders may possess “long-lived ” information sets arising from poor dissemination and disclosure of market information. The paper has two objectives: (1) to investigate a price-volume relationship for stock returns, accounting for conditional heteroscedasticity and nonlinearity; and (2) to determine whether volume is a sufficient proxy for information flow. Our results show that simple linear autoregressive models of stock returns display significant nonlinearities, which can partly be explained by functional and variable misspecification in the functions describing the mean and variance of returns. In particular, we find that prices and volume are not sufficient statistics for the conditioning information set of traders because both volume and the real effective exchange rate are significant predictors for the distribution of stock returns.

The paper compares the dynamics of global, country and industry effects in firm level returns between emerging and mature markets. Based on 1,893 firms in MSCI global index from 1990 to 2002 from 37 countries our results show that the global and industry effects are still dominated by the country effects in emerging markets in contrast to developed markets. The results are robust to controlling for variables which might have significant impact on firms ’ factor effects, such as the firm’s business globalization, financial market integration and TMT sector affiliation. Our findings have important implications for international portfolio diversification.

In this study we investigate the statistical properties of wholesale electricity spot and futures prices traded on the New York Mercantile Exchange for delivery at the California-Oregon Border. Using daily data for the years 1998 and 1999, we find that many of the characteristics of the electricity market can be viewed to be broadly consistent with efficient markets. The futures risk premium for six-month futures contracts is estimated to be about.1328 percent per day or 4 percent per month. Using a GARCH specification, we estimate minimum variance hedge ratios for electricity futures. Finally, we model the dynamic relation between spot and futures prices using both an Exponential GARCH model and a vector autoregression representation. 1

European Finance Association, DePaul/the Federal Reserve Bank of Chicago, the University of

In this paper we investigate the statistical properties of wholesale electricity spot and futures prices traded on the New York Mercantile Exchange for delivery at the California-Oregon Border. Using daily data for the years 1998 and 1999, we find that many of the characteristics of the electricity market can be viewed to be broadly consistent with efficient markets. The futures risk premium for six-month futures contracts is estimated to be 0.1328 percent per day or about 4 percent per month. Using a GARCH specification, we estimate minimum variance hedge ratios for electricity futures. Finally, we study the dynamic relation between spot and futures prices using an Exponential GARCH model and between the spot and futures returns series using a vector autoregression.

In this paper we examine under what circumstances the information accumulated during market closing time and conveyed to the price formation at market opening may be exploited to predict where the stock price will be at the end of the trading day. In our sample of three financial time series, we find that, in spite of linear uncorrelatedness, there exists a strong nonlinear dependence structure in the conditional mean of the intra-daily returns. To model this structure we use the functional-coefficient (FC) model of Cai, Fan, and Yao (2000) where the coefficients are time-varying and dependent on the state of stock return volatility. Out-of-sample forecast performances of the FC models and linear models where the coefficients are constant are also compared using the criteria of mean square forecast errors, trading returns, and directional forecasts. 1 I

A unique data set allows us to monitor the buys, sells, and holds of individuals and institutions in the Finnish stock market on a daily basis. With this data set, we employ Logit regressions to identify the determinants of buying and selling activity over a two-year period. We find evidence that investors are reluctant to realize losses, that they engage in tax-loss selling activity, and that past returns and historical price patterns, such as being at a monthly high or low, affect trading. There also is modest evidence that life-cycle trading plays a role in the pattern of buys and sells. THE EXTRAORDINARY DEGREE OF TRADING ACTIVITY in financial markets represents one of the great challenges to the field of finance. Many theoretical models in finance, such as those found in Aumann ~1976! and Milgrom and Stokey ~1982!, argue that there should be no trade at all. Empirical research by Odean ~1999! also shows that the trades of many investors not only fail to cover transaction costs, but tend to lose money before transaction costs. To

It is often presumed that higher market volatility begets more active trading in derivatives markets. A number of empirical studies have confirmed that such a positive relationship between volatility and activity exists. However, those studies have usually drawn on analyses that apply mainly to daily or intraday data. Very few studies have considered the existence of a possible relationship between volatility and volume from one month to the next. Moreover, the nature of the trading that could give rise to such a relationship is generally left unexplained. In this special feature, we examine the relationship between volatility and monthly activity in exchange-traded derivatives contracts. First, we discuss the various trading motives that would lead to such a relationship. We distinguish between hedging motives and information-based motives. Moreover, we distinguish between motives that tend to generate a relationship between volatility and volume on a day-to-day basis from those that would create a relationship on a month-to-month basis.

The paper examines the impact of margins, adjusted for underlying price risk proxied by market volatility, on trading volume and at the same time incorporates the relationship between trading volume, and price volatility documented in equities and futures markets. The study estimates bivariate GARCH-M models to take account of the inter-relationships and applies them to the Greek derivatives market over the period 1999-2005. The results show that when adjusting margins for market risk there is no impact on trading volume, casting doubts on the results of previous research, and providing support for the view that margin requirements are used only as a mechanism to prevent trader default.